Shadowing Practice: AI Agent چیست؟ راهنمای کامل ایجنتهای هوش مصنوعی از صفر - Learn English Speaking with Video
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I am just a few agents who don't want to do it and do it.
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I will show you how agent works, which is a job, which is a job,
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which is a job, which is a job
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and how to do it agent agent agent agent agent agent
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agent agent agent agent agent agent agent agent agent agent agent
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agent agent agent agent agent agent agent agent agent agent agent
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agent agent agent agent agent agent agent agent agent agent agent
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agent agent agent agent agent agent agent agent agent agent agent
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agent agent agent agent agent agent agent agent agent agent agent
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agent agent agent agent agent agent agent agent agent agent agent
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agent agent agent agent agent agent agent agent agent agent agent
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agent agent agent agent agent agent agent agent agent agent agent
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agent agent agent agent agent agent agent agent agent agent agent
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agent agent agent agent agent agent agent agent agent agent agent
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agent agent agent agent agent agent agent agent agent agent agent
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agent agent agent agent agent agent agent agent agent agent agent
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agent agent agent agent agent agent agent agent agent agent agent
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agent agent agent agent agent agent agent agent agent agent agent
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agent agent agent agent agent agent agent agent agent agent agent
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agent agent agent agent agent agent agent agent agent agent agent
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agent agent agent agent agent agent agent agent agent agent agent
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agent agent agent agent agent agent agent agent agent agent agent
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agent agent agent agent agent agent agent agent agent agent agent agent agent agent agent agent agent agent agent
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The world of a agent will be able to give you a way to the world.
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This is a way to look at 10 times.
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It's a way to get rid of them.
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And in every way, you can get rid of them.
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After video, all the agents will be able to get rid of them.
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You can see the agent will be able to get rid of them.
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So, let's go ahead and get rid of them.
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I'm going to get rid of them.
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You can tell me that you can tell me about the computer.
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If it's a computer, it's a computer.
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If it's a computer, it's a computer.
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It's a computer.
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The computer is a computer.
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When you tell me about the computer, 1000 examples show you.
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Your own computer is a computer.
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It's a computer.
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Like a computer, it's a computer.
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It's a computer.
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It's a computer.
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It's a computer.
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It's a computer and the other way, it will be a good job.
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We have three different parts of the system.
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First, the system is a law enforcement.
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The law enforcement has been outside the law.
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After the law enforcement, the machine has been out of the data.
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But every model has been just one job.
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After that, in 2017, Google has a memory transformer.
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This is the same way that it has been in GPT and Cloud.
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The difference between the models is that
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Model -a -y -q -d -m -e -y,
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This is the most important part of this video.
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You can't wait to write it until you leave it.
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You can't answer it and you can't answer it.
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And you can't wait to get it.
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It's just a way to get it.
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Without a cadre, you can't do it.
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You can't file, email, check it out.
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You can't do it.
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Agent, you have to do it and do it.
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You can't do it.
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You can't do it
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and on a single step of the step of the step
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of the step of the step of the step of the
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step of the step of the step of the step of
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the step of the step of the step of the step
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of the step of the step of the step of the
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step of the step of the step of the step of
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the step of the step of the step of the step
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of the step of the step of the step of the
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step of the step of the step of the step of
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the step of the step of the step of the step
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of the step of the step of the step of the
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step of the step of the step of the step of
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the step of the step of the step of the step
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of the step of the step of the step of the
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step of the step of the step of the step of
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the step of the step of the step of the step
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of the step of the step of the step of the
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step of the step of the step of the step of
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the step of the step of the step of the step
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of the step of the step of the step of the step of the three things that we have to give.
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In the way, it's a way to get into it.
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It's a way to get into it.
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And it's a way to get into it.
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This is a way to get into it.
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It's a way to get into it.
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It's a way to get into it.
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It's a way to get into it.
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Only one of them can do it.
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We have to get into it.
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I have to get into it.
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There's a way to get into it.
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workflow workflow means that you can use the first step
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model to you work but it does not mean to be done by the way
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because you can use the work flow and the most important work flow is done
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better because it is a simple and easy way and the way you can use the work flow workflow
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agent when you get to the steps you don't know and you need to get a process
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I have to do a video I have to do a video I have to do a workflow
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and do a chat and do a workflow and do a chat I have to do a
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video I have to video I have to do a video .
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It's 4 -4.
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It's a way to do it.
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It's a way to do it.
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It's a way to do it.
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It's a way to do it.
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For example, you can do it.
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You can do it.
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You can do it.
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You can do it.
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You can do it.
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You can do it.
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You can do it.
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I'll see you next time.
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I would like to like this video,
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like this video, subscribe and subscribe to my channel and make sure you can do it.
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Because I can't do it.
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It can be a very similar experience in my life.
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Absor and Function Calling Agent can only be done with a single job.
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and then the name of the app is the app.
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Model when you have a number of them, the model is a number of them, the model is a number of them,
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which is a number of them.
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The model is called the model.
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The model is a number of them, which is a number of them, which is a number of them,
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and the model is a number of them.
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Let's go ahead and get them to the model.
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You can't ask them, what is the model?
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Model is a number of them, which is the model.
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This model is a number of them.
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The model is a number of them, which is the model.
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The program you can use the service of the data.
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Data will be able to get the data and the data will be able to use it.
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You can use it.
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3 -3 and 3 -3.
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But you can only one answer.
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One important question is that you can't really apply.
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The model is the model.
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The model is the model.
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The model is the model.
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The model is the model.
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and the model will be more effective.
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The model will be more effective.
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The model will be more effective.
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This is a project that you can do with the project.
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This is a project that you can do with the project.
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So, the project will be more effective.
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The project will be more effective.
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The project will be more effective.
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The project will be more effective.
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The project will be more effective.
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The project will be more effective and now it's now
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This is the chat that you can see before which is
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because it's a way that every time the previous one is a
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but one thing is is a way to the context window
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is there are two things
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First of all, you need to get a thing to do.
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Two, you need to get a thing to do.
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You need to get a thing to do.
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Because every time you get a thing to do, you need to get a thing to do.
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When you do a chat, you don't have to do it.
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You need to do it.
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You need to do it.
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The thing you can do to model is The thing
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you can do to model is The thing you can do to token
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But you can do to make a way of the agent
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Every door of the way of the agent
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The way of the agent is to give you 10 to 10, 10 times more
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For the agent to get rid of them
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This is the way of the agent
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This is the way of the agent
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One is the 5th century you can see just some other points
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and then you can see it very quickly
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and this is a way of making a model
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when the model is a model of the model is a model and it will be a model
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but it will be a model but it will be a model ...
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I'll add a bit of a balance of the balance of
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the balance of the balance of the balance of the balance
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of the balance of the balance of the balance of the
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balance of the balance of the balance of the balance of
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the balance of the balance of the balance of the balance
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of the balance of the balance of the balance of the
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balance of the balance of the balance of the balance of
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the balance of the balance of the balance of the balance
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of the balance of the balance of the balance of the
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balance of the balance of the balance of the balance of
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the balance of the balance of the balance of the balance
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of the balance of the balance of the balance of the
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balance of the balance of the balance of the balance of
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the balance of the balance of the balance of the balance
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of the balance of the balance of the balance of the
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balance of the balance of the balance of the balance of
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the balance of the balance of the balance of the balance
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of the balance of the balance of the balance of the
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balance of the balance of the balance of the balance of
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the balance of the balance of the balance of the balance of the and the first one must be beyond the screen.
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And again, when 1000 ticks, the screen is written by the screen.
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For this question, we will see the embedding vector database.
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The results are in the same period.
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First, embedding.
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I'll tell you,
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you can't imagine.
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Now I'll give you a computer.
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Computer doesn't understand, but it's not a problem.
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P .S.
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M .O.
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M .O.
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M .O.
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M .O.
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M .O.
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M .O.
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M .O.
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M .O.
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M .O.
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M .O.
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M .O.
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M .O.
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M .O.
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M .O.
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M .O.
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M .O.
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M .O.
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M .O.
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M .O.
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M .O.
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M .O.
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I mean first one, then after the answer, then after the answer, then after the answer,
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the question is that the question is that the answer is
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that the answer is that the answer is that the answer is
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that the answer is that the answer is that the answer is
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that the answer is that the answer is that the answer is
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that the answer is that the answer is that the answer is
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that the answer is that the answer is that the answer is
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that the answer is that the answer is that the answer is
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that the answer is that the answer is that the answer is
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that the answer is that the answer is that the answer is
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that the answer is that the answer is that the answer is
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that the answer is that the answer is that the answer is
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that the answer is that the answer is that the answer is
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that the answer is that the answer is that the answer is
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that the answer is that the answer is that the answer is
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that the answer is that the answer is that the answer is
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that the answer is that the answer is that the answer is
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that the answer is that the answer is that the answer is and when you get a model, you can do it again.
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You can do it again.
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You can do it.
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I'm going to give you a quick look.
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The effect of the product is a model.
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It's a way to make it.
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The name of this is Chunking.
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The product is very powerful.
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The product is very powerful.
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The product is very powerful and use this to help the problem.
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It is that the key has been one way to do it.
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So after all the key, it is a character of the key after the key.
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If it is a question of the key, it will be a way to get it.
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And it will be a way to get it.
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It will be a way to get it.
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It will be a way to get it.
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Because this model is a way to get it.
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The key is that the key is the key something that is good.
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If the ticket is correct, the model will be automatically correct.
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7 MCP 2 -SK have been talking about the app.
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This app is only one app.
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It is only one app.
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If you want to make it
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Agent -EVAC, and then again, we need to use this.
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MCP is this problem.
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The name is Model Context Protocol.
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It is a standard for the ability to use the model to use the model.
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MCP is a port of USP of the world.
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Before, it was a cable that had to be.
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However, it was standard for all of them to use the model.
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After all the agent can understand the protocol, can be able to get it.
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The reason why is that every server you can use the system to make it.
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Server of the national security system will not be able to use it.
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I will show you a video that I will show you a little bit.
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You can see the link below the 6th link.
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The memory.
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We will get the rest of the questions.
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We will get the 2nd page.
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We will be able to get these things to do
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and get them to be able to get them to get
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them to get them to get them to get them to
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get them to get them to get them to get them
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to get them to get them to get them to get
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them to get them to get them to get them to
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get them to get them to get them to get them
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to get them to get them to get them to get
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them to get them to get them to get them to
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get them to get them to get them to get them
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to get them to get them to get them to get
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them to get them to get them to get them to
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get them to get them to get them to get them
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to get them to get them to get them to get
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them to get them to get them to get them to
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get them to get them to get them to get them
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to get them to get them to get them to get
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them to get them to get them to get them to
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get them to get them to get them to get them
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to get them to get them to get them to get them to get them
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and then the list of the steps will be made
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and then the steps will be made and then the steps will be made
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For the steps of the steps, the steps will be made and the steps will be made
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If you have a step to the steps, you can see the steps that you can see the steps
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The steps will be made and the steps will be made and the steps will be made and the other way,
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the first one is the real thing.
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The first one is the first list of the file file.
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Then the first one is the tick and the second one is the tick.
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The third one is the orchestrator and worker.
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The agent is the agent that has been working with several agents.
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The other one is the agent that has been working with them.
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The fourth one is the agent's work
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and agent to create a new agent to create a new agent
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and then the new agent is to create a new agent is to create a new agent
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and then the agent is to create a new agent
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and then the agent is to create a new agent
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and then the agent is to create a new agent
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If you have an agent with 20 adsor and 10 -10 pages, then you can use one thing to do.
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The result is agent that you can't do anything to do.
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The result is that agent is a few agents that have been done.
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One is only one who can do it, one who can do it, one who can do it.
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Every single one of those adsor and other things, they can do it.
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Let's put a example on that you can do better.
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If you want to make a system that you can do it, you can do it.
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Agent 1.
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Agent 2.
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Agent 2.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent 3.
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Agent The reason why is this is that the house is a bit different and the whole thing is a bit different.
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With the one who is working, you can actually work with a few agents.
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Framework is a bit different from the framework.
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Framework is a bit different from agent.
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It is a way to make a way to make a way to make a way to make it easier.
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It is a good idea that you can use framework.
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It is a good idea that you can use framework.
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It is a good idea that you can use framework.
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It is a good idea that you can use framework.
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which is a good idea that you can use.
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It is a good idea that you can use framework which is a good idea.
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It is a good idea that you can use framework
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which is a good idea that you can use framework and you can use it to use it.
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It is a good idea that you can use it
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It's time to be a agent with a few agents.
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Second, the SDK of the company.
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Like OpenAI, Google and Anthropic.
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They have a few of them.
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They have a few of them.
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They have a few of them.
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They have a few of them.
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But they can be able to get them.
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The choice is this.
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If you want to make a model, you can't do it.
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If you want to make a model, if you want to make a model, you can't do it.
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If you want to make a model, you can't do it.
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If you want to make a model, you can't do it.
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If you want to make a model, you can't do it.
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If you want to make a model, you can't do it.
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If you want to make a model, you can't do it.
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If you want to make a model, you can't do it.
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If you want to make a model, you can't do it.
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If you want to make a model, you can't do it.
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If you want to make a model, you can't do it.
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If you want to make a model, you can't do it.
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If you want to make a model, you can't do it.
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If you want to make a model, you can't do it.
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If you want to make a model, you can't do it.
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If you want to make
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He has now a place where he works and works and works.
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There are several people who have been in front of this journey that are the agents that have been made.
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In the past, the most important place is to answer the agents.
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For example, an agent email, agent who is a result of the and the email will send it to you.
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At the side of their agent, they will be able to send it to you.
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At the side of their agent, they will be able to send it to you.
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In this video, the agent will be able to send it to you.
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The agent will be able to send it to you, and if it is a mistake, it will be able to send it to you.
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We will be able to get the first video to the channel.
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In the market, the agent will be able to give the video to the channel.
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This is the most important thing.
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It's a thing that's all.
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It's a thing that's a thing.
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It's a thing that's a thing that's a thing.
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We have to get started.
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but it is not a way to do it.
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And one thing that I have to do is to do it.
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And one thing that I have to do is to do it.
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Some of the things that I have to do is to do it.
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But the security is one thing that I have to do it.
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This is a way to do it.
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This is a way to do it.
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It's a way to do it.
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It's called Prompt Injection.
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It's a way to do it.
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It's a way to do it.
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It's a way to do it.
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It's a way to do it beifte bera.
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Fرض kene agent dare yuhye safhwe webo mikhonhe.
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Vosat aumon safhwe yuhye mtn nomarii nvwishhe shude khe humye dastoriy
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qablii ro nadeed begiru mhutwae failea ro bifrist be aen adres agent farki bane dastor to wa mtn aumsofhe gail nemie shhe.
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Aghe mhafazat nedash tebashi mmknhe waqan einkar ro beraet beraet anjame dhe.
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Aenam yuhye seneoriya خیب waqai bude.
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Khatr dvom gostarish dama manhaz.
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Behish
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and then it will be a new one
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and will be a new one and will be a new one and in the third one, the video is a new one 4.
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the way of the health care is to be able to
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do this first one is a new one before the agent
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second one is a new one before the agent before the
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agent is to be able to do this third one is a new one
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It's just a way to get into a situation.
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If you have a job, you can't be a agent voice and you can't be a type.
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4 -Rumny, a code is only within a moment of isolation.
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It's a way that you can't put your system in the moment.
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You can't put your own side to the side.
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You can't see that agent in every step what you think and what you think.
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Without this, the debugger is actually not possible.
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There are 4 times that you have to do it and how much money you can do it.
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How many percent of your work are working?
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How many steps are working?
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How many steps are working?
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How many steps are working?
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And the last thing I would like to give you and I would like to give you a agent to your test.
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You can use a test or you can use 20 -20 to make a test with the answer that you know.
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Every time you have a prompt or a result you have to request do you again?
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without this, you can see it is a problem
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the way we have to do it let's go ahead
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and do it we have to go ahead we have to go ahead
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we have to go ahead we have to go ahead
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we have to go ahead we have to go ahead we have to go ahead we have to go ahead
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and we have to go ahead and we have to go ahead
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and we have to go ahead and we have to go ahead and we will see how this is going to be.
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Finally, in the entire way, we will see a guardrail that will be able to get rid of the car.
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Now, you have to go through three steps.
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First, the first step is to go through the next step.
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The first step is to go through the entire list.
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The second step is to go through the description.
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The second step is to go through the first agent.
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One step is to go through the next step and then you can also create a new version of the app.
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Do you have a new version of the app?
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Do you have a new version of the app?
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Do you have a new version of the app?
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Do you have a new version of the app?
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This was the whole thing that one agent should be able to do.
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Very happy to have you in this video.
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In the video, we will have to make a video about the agent.
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For the agent, we will need to make a video about the agent.
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For the agent, we will need to make a video about the agent.
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We will need to make a video about the agent.
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If you want to make a video about the agent,
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we will need to make a video about the agent.
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We will need to make a video about the agent.
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We will need to make a video about the agent.
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I can't believe that you can do this video and you can do it.
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I'll see you in the next video.
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I'll see you in the next video.
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Vocabulario y notas de pronunciación para esta lección
Esta lección de conversación se basa en el vídeo “AI Agent چیست؟ راهنمای کامل ایجنتهای هوش مصنوعی از صفر”. Las palabras que más se repiten: agent, step, balance, model, answer. Este vídeo tiene 526 frases y 4510 palabras para practicar shadowing. La parte hablada dura 25:19. El hablante habla a un ritmo natural de unas 178 palabras por minuto, cercano a una conversación cotidiana. El 91 % de las palabras está entre las 3.000 más comunes del inglés, por lo que el vocabulario es fácil de seguir.
Vocabulario clave de este vídeo
15 palabras del vídeo que vale la pena aprender, con su pronunciación y significado:
| Palabra | Pronunciación | Significado |
|---|---|---|
| framework sustantivo | /ˈfɹeɪm.wɜːk/ | entramado, armazón |
| enforcement sustantivo | /ɪnˈfoɹsm(ə)nt/ | enforzamiento |
| tick sustantivo | /tɪk/ | garrapata, rezno |
| server sustantivo | /ˈsɝvɚ/ | servidor |
| subscribe verbo | /səbˈskɹaɪb/ | suscribirse, subscribirse |
| prompt verbo | /pɹɑmpt/ | llevar a, concitar |
| bone sustantivo | /boʊn/ | hueso |
| worker sustantivo | /ˈwɝ.kɚ/ | trabajador, obrero |
| dare verbo | /dɛ(ə)ɹ/ | osar, atreverse |
| database sustantivo | /ˈdeɪtəˌbeɪs/ | base de datos, banco de datos |
| keen adjetivo | /kin/ | entusiasta, ardoroso |
| isolation sustantivo | /ˌaɪsəˈleɪʃən/ | aislamiento, soledad |
| vector sustantivo | /ˈvɛktɚ/ | vector |
| token sustantivo | /ˈtoʊkən/ | seña |
| embed verbo | /ɪmˈbɛd/ | embutir, empotrar |
Phrasal verbs que vas a escuchar
| Palabra | Pronunciación | Significado |
|---|---|---|
| go ahead verbo | /ˌɡoʊ əˈhɛd/ | venga, adelante |
| go through verbo | atravesar |
Frases que vale la pena repetir
Frases cortas y completas del vídeo que puedes reutilizar en la conversación diaria:
- I'm going to get rid of them.
- You can't answer it and you can't answer it.
- You can't ask them, what is the model?
- How many percent of your work are working?
- Do you have a new version of the app?
Gramática en este vídeo
Las estructuras que más usa el hablante, con las palabras exactas del vídeo:
| Estructura | En el vídeo |
|---|---|
| Present perfect continuous have/has been + -ing — una acción que empezó antes y continúa | have been talking · has been working |
| Oraciones condicionales if + oración, will/would + verbo — una condición y su resultado | if it is a mistake, it will be |
| Voz pasiva be + participio pasado — importa lo que ocurre, no quién lo hace | be done · is called · is written |
| Oraciones de relativo who / which + oración — información extra sobre una persona o cosa | works, which is · job, which is · them, which is |
Pronunciación a tener en cuenta
El hablante usa 47 contracciones y formas reducidas, como can't, I'll, don't. Dilas en su forma corta, tal como las oyes.
Sonidos difíciles para hispanohablantes:
- /v/ — no es /b/: los dientes tocan el labio inferior: server /ˈsɝvɚ/, vector /ˈvɛktɚ/
Cómo practicar con este vídeo
- Escucha el vídeo entero una vez sin hablar y anota las palabras que no conoces.
- Empieza a velocidad 0,75×, haz shadowing frase por frase y vuelve a la velocidad normal cuando te resulte fácil.
- Grábate y compara con el original, prestando atención a palabras como framework, enforcement, tick.
¿Qué es la Técnica de Shadowing?
Shadowing es una técnica de aprendizaje de idiomas respaldada por la ciencia, desarrollada originalmente para la formación de intérpretes profesionales y popularizada por el políglota Dr. Alexander Arguelles. El método es simple pero poderoso: escuchas audio en inglés nativo y lo repites en voz alta de inmediato, como una sombra que sigue al hablante con solo 1-2 segundos de retraso. A diferencia de la escucha pasiva o los ejercicios de gramática, el shadowing obliga a tu cerebro y músculos de la boca a procesar y reproducir simultáneamente patrones de habla reales. Las investigaciones muestran que mejora significativamente la precisión de la pronunciación, la entonación, el ritmo, el habla conectada, la comprensión auditiva y la fluidez al hablar, convirtiéndola en una de las metodologías más efectivas para la preparación del IELTS Speaking y la comunicación en inglés en el mundo real.